The Challenge of Climate Modeling and its Importance in our Understanding Global Climate Change.
Working at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) at Princeton University was one of the most challenging and rewarding experiences I have ever had. It was a challenge because it involved becoming proficient in computer science and programming for climate sciences...and before this research internship I had never even attempted to turn on a scientific computer! It was rewarding because in less than three months I not only learned how to work with scientific computers, but I generated hundreds of maps, got to interact with world-renown scientists and most importantly understood how crucial is climate modeling for our awareness and adaptation plans as we face global climate change.
My research at GFDL involved benchmarking ocean biogeochemical fields in the laboratory's Earth System Models. Scroll below to view some of my work products.
Comparing PO4 levels in the ocean: Historical Observations vs. Model Levels
To asses how accurate GFDL's Earth System Models are at representing nutrient levels in the ocean it is useful to generate maps that compare historical levels (obtained through observations) with output from the model. My work at GFLD focused on generating comparison maps and doing these type of analyzes. By observing differences visually, we can identify trends that might point out how the model is behaving differently from reality and propose changes that can potentially lead to more accurate model representation. It is also important to be aware of these differences because they can have an influence on other variables that are modeled (e.g. nutrients, chlorophyll, etc..) The document below is a comparison map of oceanic phosphate (PO4) levels from observations vs. oceanic PO4 levels from GFDL's Earth System Model.
Benchmarking Ocean Biogeochemical Fields in GFDL's Earth Systems Models
The goal of benchmarking ocean biogeochemical fields in the models is to create diagnostics that help scientists see model biases and simplify some processes to be able to monitor the behavior of the model regularly. This has implications for climate change modeling and it matters because we rely on the information given by this models to guide policy and research aimed at mitigating the impacts of climate change. The more accurate models can be, the better they serve as tools to understand our present and plan our future.
The final product of my research at NOAA's GFDL was a presentation detailing my analysis of ocean biogeochemistry fields in the Earth Systems Model.